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Clinical relevance of lymph node ratio in resected oral cavity squamous cell carcinoma in patients with N2 disease.

2016· article· en· W2695844310 on OpenAlexaff
Ali Hosni, David P. Goldstein, Shao Hui Huang, Wei Xu, Yuyao Song, Andrew Bayley, Scott V. Bratman, John Cho, Meredith Giuliani, John Kim, Jolie Ringash, John Waldron, Patrick Gullane, Ralph Gilbert, Jonathan C. Irish, Brian O’Sullivan, Andrew Hope

Bibliographic record

VenueJournal of Clinical Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicinePerineural invasionLymphovascular invasionLymph nodeNeck dissectionLymphChemotherapyRadiation therapyInternal medicineRetrospective cohort studyMetastasisGastroenterologyCancerOncologyUrologyPathology

Abstract

fetched live from OpenAlex

6019 Background: Lymph node ratio (LNR, number of positive lymph nodes/total number of excised lymph nodes) has been shown to be associated with outcomes in multiple malignancies. In this study, the impact of LNR on distant metastasis (DM) and overall survival (OS) in oral cavity squamous cell carcinoma (OSCC) was investigated. Methods: Retrospective review of pN0-2 OSCC patients (pts) treated between 1994-2012 with curative surgery with neck dissection (ND) +/- postoperative radiotherapy (PORT) with or without concurrent chemotherapy (CCT). LNR was subjected to multivariable analysis (MVA) of DM and OS, adjusted for pT3-4, extracapsular extension (ECE), high grade (G3), lymphovascular invasion (LVI), perineural invasion (PNI), and tumor subsite. Results: Overall 914 pts were identified; median age: 61 yr (18-92); median follow-up: 51 months (1–189); pT3-4: 283 (31%); pN-classification: N0: 482 (53%), N1: 128 (14%), N2a: 6 (0.5%); N2b: 225 (24.5%); N2c: 73 (8%); median number of dissected nodes: 36 (6-125); median number of pN+: 2 (1-49); median LNR for pN+ pts: 0.06; ECE: 187 (20%); G3: 147 (16%); LVI: 115 (13%); PNI: 416 (46%). Bilateral ND was performed in 367 (40%); PORT was used in 452 (49%); and CCT in 80 (9%). The 5-yr distant control (DC) and OS were 89% and 70%; respectively. pT3-4 (p<0.001), G3 (p<0.001), LVI (p=0.0013), and PNI (p<0.001) were all associated with high LNR. On MVA, LNR >0.06 was associated with more DM (HR=1.8; 95%CI=1.1-3.1; p=0.017) and lower OS (HR=2; 95%CI=1.4–2.8; p<0.001). In subgroup analysis of pN2 pts (n=304): higher LNR (>0.14) was associated with lower 5yr- DC (67%, p=0.014) and OS (25%, p<0.001), and on MVA within the pN2 subgroup, both higher LNR (p<0.001) and ECE (p=0.006) were associated with lower OS. Conclusions: High LNR is associated with higher rate of DM and lower OS in OSCC. LNR should be assessed in pN2 pts in future prospective trials to select patients for adjuvant therapies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.066
GPT teacher head0.418
Teacher spread0.352 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
Admission routes1
Has abstractyes

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